This notebook contains a set of analyses for analyzing daves’s boardgamegeek collection. The bulk of the analysis is focused on building a user-specific predictive model to predict the games that the specified user is likely to own. This enables us to ask questions like, based on the games the user currently owns, what games are a good fit for their collection? What upcoming games are they likely to purchase?
We can look at a basic description of the number of games that the user owns, has rated, has previously owned, etc.
What years has the user owned/rated games from? While we can’t see when a user added or removed a game from their collection, we can look at their collection by the years in which their games were published.
We can look at the most frequent types of categories, mechanics, designers, and artists that appear in a user’s collection.
We’ll examine predictive models trained on a user’s collection for games published through 2020. How many games has the user owned/rated/played in the training set (games prior to 2020)?
username | dataset | period | games_owned | games_rated |
daves | training | published before 2020 | 131 | 55 |
daves | validation | published 2020 | 0 | 0 |
daves | test | published after 2020 | 0 | 0 |
The main outcome we will be modeling for the user is owned, which refers to whether the user currently owns or has a previously owned a game in their collection. Our goal is to train a predictive model to learn the probability that a user will add a game to their collection based on its observable features. This amounts to looking at historical data and looking to find patterns that exist between features of games and games present in the user’s collection.
One of the models we trained was a decision tree, which looks for decision rules that can be used to separate games the user owns from games they don’t. The resulting model produces a decision corresponding to yes or no statements: to explain why the model predicts the user to own game, we start at the top of the tree and follow the rules that were learned from the training data.
Note: the tree below has been further pruned to make it easier to visualize.
Decision trees are highly interpretible models that are easy to train and can identify important interactions and nonlinearities present in the data. Individual trees have the drawback of being less predictive than other common models, but it can be useful to look at them to gain some understanding of key predictors and relationships found in the training data.
We can examine coefficients from another model we trained, which is a logistic regression with elastic net regularization (which I will refer to as a penalized logistic regression). Positive values indicate that a feature increases a user’s probability of owning/rating a game, while negative values indicate a feature decreases the probability. To be precise, the coefficients indicate the effect of a particular feature on the log-odds of a user owning a game.
Why did the model identify these features? We can make density plots of the important features for predicting whether the user owned a game. Blue indicates the density for games owned by the user, while grey indicates the density for games not owned by the user.
Binary predictors can be difficult to see with this visualization, so we can also directly examine the percentage of games in a user’s collection with a predictor vs the percentage of all games with that predictor.
% of Games with Feature | ||||
username | Feature | User_Collection | All_Games | Ratio |
daves | Alderac Entertainment Group | 6.9% | 0.7% | 9.58 |
daves | Asmodee | 22.9% | 2.5% | 9.10 |
daves | Wizards Of The Coast | 4.6% | 0.5% | 8.50 |
daves | Fantasy Flight Games | 8.4% | 1.1% | 7.34 |
daves | Pegasus Spiele | 15.3% | 2.1% | 7.12 |
daves | Unknown | 5.3% | 0.9% | 6.22 |
daves | Rio Grande Games | 9.2% | 1.9% | 4.84 |
daves | Artist Oliver Freudenreich | 3.1% | 0.6% | 4.80 |
daves | Deduction Game | 19.1% | 5.0% | 3.79 |
daves | Bluffing | 19.8% | 5.7% | 3.50 |
daves | Kosmos | 6.1% | 2.0% | 3.10 |
daves | Word Game | 6.9% | 2.2% | 3.07 |
daves | Party Game | 23.7% | 9.3% | 2.55 |
daves | Variable Setup | 1.5% | 1.4% | 1.06 |
daves | Crowdfunding Kickstarter | 5.3% | 12.7% | 0.42 |
daves | Movies TV Radio Theme | 0.8% | 5.0% | 0.15 |
Before predicting games in upcoming years, we can examine how well the model did and what games it liked in the training set. In this case, we used resampling techniques (cross validation) to ensure that the model had not seen a game before making its predictions.
Displaying the 100 games from the training set with the highest probability of ownership, highlighting in blue games the user has owned.
Rank | Published | ID | Name | Pr(Owned) | Owned |
1 | 1990 | 2944 | Halli Galli | 0.795 | no |
2 | 2011 | 70919 | Takenoko | 0.787 | no |
3 | 2014 | 163412 | Patchwork | 0.609 | no |
4 | 2005 | 18723 | Aye, Dark Overlord! The Red Box | 0.588 | no |
5 | 2003 | 6472 | A Game of Thrones | 0.570 | no |
6 | 2017 | 230059 | Crossfire | 0.547 | no |
7 | 1998 | 20832 | Halli Galli Junior | 0.512 | no |
8 | 2018 | 259809 | Sonar Family | 0.468 | no |
9 | 2016 | 171131 | Captain Sonar | 0.459 | yes |
10 | 2013 | 127024 | Room 25 | 0.448 | no |
11 | 2010 | 65272 | Cyrano | 0.435 | no |
12 | 2019 | 272453 | KeyForge: Age of Ascension | 0.434 | no |
13 | 2018 | 257501 | KeyForge: Call of the Archons | 0.429 | no |
14 | 2010 | 82702 | Funfair | 0.429 | no |
15 | 1993 | 1234 | Once Upon a Time: The Storytelling Card Game | 0.414 | no |
16 | 1988 | 550 | Barbarossa | 0.407 | no |
17 | 2017 | 216658 | Smash Up: What Were We Thinking? | 0.398 | no |
18 | 2011 | 96848 | Mage Knight Board Game | 0.395 | no |
19 | 2016 | 198487 | Smash Up: Cease and Desist | 0.395 | no |
20 | 2013 | 134726 | Smash Up: Awesome Level 9000 | 0.392 | yes |
21 | 2016 | 205637 | Arkham Horror: The Card Game | 0.365 | no |
22 | 1994 | 18 | RoboRally | 0.360 | no |
23 | 2012 | 124742 | Android: Netrunner | 0.360 | yes |
24 | 1998 | 116 | Guillotine | 0.359 | no |
25 | 2019 | 283863 | The Magnificent | 0.355 | no |
26 | 2017 | 220775 | Codenames: Disney – Family Edition | 0.354 | no |
27 | 2005 | 16226 | Gone Fishing! | 0.353 | no |
28 | 2015 | 162559 | Smash Up: Munchkin | 0.347 | no |
29 | 1993 | 463 | Magic: The Gathering | 0.345 | no |
30 | 2009 | 45134 | Arcana | 0.340 | yes |
31 | 2010 | 65200 | Asteroyds | 0.333 | no |
32 | 2002 | 3955 | BANG! | 0.331 | no |
33 | 2009 | 56885 | The Werewolves of Miller's Hollow: The Village | 0.324 | no |
34 | 2018 | 242639 | Treasure Island | 0.322 | no |
35 | 2014 | 160018 | Smash Up: Monster Smash | 0.317 | no |
36 | 2005 | 15062 | Shadows over Camelot | 0.314 | no |
37 | 2015 | 178900 | Codenames | 0.314 | yes |
38 | 2017 | 216199 | Smash Up: Big in Japan | 0.310 | no |
39 | 2005 | 19237 | Ca$h 'n Gun$ | 0.309 | no |
40 | 2016 | 198773 | Codenames: Pictures | 0.308 | no |
41 | 2013 | 143741 | BANG! The Dice Game | 0.305 | yes |
42 | 2001 | 3495 | Harry Potter Trading Card Game | 0.293 | no |
43 | 2000 | 478 | Citadels | 0.288 | no |
44 | 2007 | 30324 | Ca$h 'n Gun$: Live | 0.266 | no |
45 | 2012 | 85394 | The Last Banquet | 0.260 | no |
46 | 1999 | 204 | Stephenson's Rocket | 0.258 | no |
47 | 2015 | 182694 | Watson & Holmes | 0.250 | no |
48 | 1984 | 382 | Heimlich & Co. | 0.250 | no |
49 | 2001 | 1345 | Genoa | 0.240 | no |
50 | 2017 | 190082 | Whitehall Mystery | 0.239 | no |
51 | 2018 | 241225 | Smash Up: That '70s Expansion | 0.239 | no |
52 | 1968 | 7262 | Top Trumps | 0.235 | no |
53 | 2012 | 122522 | Smash Up | 0.229 | yes |
54 | 2010 | 25292 | Merchants & Marauders | 0.229 | no |
55 | 2004 | 10547 | Betrayal at House on the Hill | 0.227 | no |
56 | 2010 | 65515 | Nuns on the Run | 0.223 | no |
57 | 2011 | 59959 | Letters from Whitechapel | 0.221 | no |
58 | 2016 | 205398 | Citadels | 0.220 | no |
59 | 2000 | 826 | Cartagena | 0.219 | no |
60 | 2016 | 205158 | Codenames: Deep Undercover | 0.213 | no |
61 | 1995 | 3072 | Necromunda | 0.209 | no |
62 | 1977 | 2593 | Pass the Pigs | 0.206 | yes |
63 | 2019 | 270168 | Tuki | 0.205 | no |
64 | 2019 | 281946 | Aftermath | 0.197 | no |
65 | 2008 | 38453 | Space Alert | 0.192 | no |
66 | 2016 | 156858 | Black Orchestra | 0.190 | no |
67 | 1997 | 11 | Bohnanza | 0.189 | yes |
68 | 2002 | 4390 | Carcassonne: Hunters and Gatherers | 0.187 | no |
69 | 1995 | 46 | Medici | 0.186 | no |
70 | 2019 | 270971 | Era: Medieval Age | 0.186 | no |
71 | 2017 | 174430 | Gloomhaven | 0.183 | no |
72 | 2007 | 31481 | Galaxy Trucker | 0.182 | yes |
73 | 2016 | 198454 | When I Dream | 0.181 | yes |
74 | 2019 | 274590 | Smash Up: World Tour – Culture Shock | 0.180 | no |
75 | 2009 | 39683 | At the Gates of Loyang | 0.180 | no |
76 | 2010 | 39242 | Black Friday | 0.176 | no |
77 | 2004 | 9220 | Saboteur | 0.176 | yes |
78 | 2001 | 6346 | NBA Showdown | 0.176 | no |
79 | 2018 | 257321 | Gen7: A Crossroads Game | 0.171 | no |
80 | 2014 | 152241 | Ultimate Werewolf | 0.168 | no |
81 | 2008 | 37046 | Ghost Stories | 0.168 | no |
82 | 1982 | 2511 | Sherlock Holmes Consulting Detective: The Thames Murders & Other Cases | 0.166 | no |
83 | 1997 | 2901 | GolfMania | 0.162 | no |
84 | 2016 | 205716 | New Angeles | 0.161 | no |
85 | 2012 | 131357 | Coup | 0.161 | yes |
86 | 2012 | 129622 | Love Letter | 0.158 | yes |
87 | 1998 | 3488 | C-23 | 0.156 | no |
88 | 2001 | 1927 | Munchkin | 0.155 | yes |
89 | 1998 | 891 | Cranium | 0.154 | no |
90 | 2011 | 92415 | Skull | 0.153 | no |
91 | 1800 | 45 | Perudo | 0.151 | no |
92 | 1997 | 436 | Canyon | 0.150 | no |
93 | 2009 | 54998 | Cyclades | 0.148 | no |
94 | 2004 | 9609 | War of the Ring | 0.148 | no |
95 | 2000 | 986 | Babel | 0.146 | no |
96 | 2015 | 191894 | Imagine | 0.145 | no |
97 | 2017 | 236475 | Best of Werewolves of Miller's Hollow | 0.145 | no |
98 | 2011 | 104347 | Santiago de Cuba | 0.145 | no |
99 | 1998 | 3 | Samurai | 0.142 | no |
100 | 1998 | 1037 | Deadlands: Doomtown | 0.140 | no |
This section contains a variety of visualizations and metrics for assessing the performance of the model(s) during resampling. If you’re not particularly interested in predictive modeling, skip down further to the predictions from the model.
An easy way to examine the performance of classification model is to view a separation plot. We plot the predicted probabilities from the model for every game (from resampling) from lowest to highest. We then overlay a blue line for any game that the user does own. A good classifier is one that is able to separate the blue (games owned by the user) from the white (games not owned by the user), with most of the blue occurring at the highest probabilities (right side of the chart).
We can more formally assess how well each model did in resampling by looking at the area under the receiver operating characteristic curve. A perfect model would receive a score of 1, while a model that cannot predict the outcome will default to a score of 0.5. The extent to which something is a good score depends on the setting, but generally anything in the .8 to .9 range is very good while the .7 to .8 range is perfectly acceptable.
wflow_id | .metric | .estimator | .estimate |
GLM | roc_auc | binary | 0.84 |
Decision Tree | roc_auc | binary | 0.69 |
Another way to think about the model performance is to view its lift, or its ability to detect the positive outcomes over that of a null model. High lift indicates the model can much more quickly find all of the positive outcomes (in this case, games owned or played by the user), while a model with no lift is no better than random guessing. A gains chart is another way to view this.
While we are probably more interested in the lift provided by the models to evaluate their efficacy, we can also explore the optimal cutpoint if we wanted to define a hard threshold for identifying games a user will own vs not own.
The threshold we select depends on how we much we care about false positives (games the model predicts that the user does not own) vs false negatives (games the user owns that the model does not predict). We can toggle threshold to
Finally, we can understand the performance of the model by examining its calibration. If the model assigns a probability of 5%, how often does the outcome actually occur? A well calibrated model is one in which the predicted probabilities reflect the probabilities we would observe in the actual data. We can assess the calibration of a model by grouping its predictions into bins and assessing how often we observe the outcome versus how often our model expects to observe the outcome.
A model that is well calibrated will closely follow the dashed line - its expected probabilities match that of the observed probabilities. A model that consistently underestimates the probability of the event will be over this dashed line, be a while a model that overestimates the probability will be under the dashed line.
What games does the model think daves is most likely to own that are not in their collection?
Published | ID | Name | Pr(Owned) | Owned |
1990 | 2944 | Halli Galli | 0.795 | no |
2011 | 70919 | Takenoko | 0.787 | no |
2014 | 163412 | Patchwork | 0.609 | no |
2005 | 18723 | Aye, Dark Overlord! The Red Box | 0.588 | no |
2003 | 6472 | A Game of Thrones | 0.570 | no |
What games does the model think daves is least likely to own that are in their collection?
Published | ID | Name | Pr(Owned) | Owned |
2000 | 904 | Dream Factory | 0.001 | yes |
2015 | 159109 | XenoShyft: Onslaught | 0.001 | yes |
1993 | 317 | The Mob | 0.001 | yes |
2013 | 140343 | Carnival Zombie | 0.001 | yes |
2013 | 137649 | Level 7 [Omega Protocol] | 0.002 | yes |
Top 25 games most likely to be owned by the user in each year, highlighting in blue the games that the user has owned.
rank | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
1 | Android: Netrunner | Room 25 | Patchwork | Smash Up: Munchkin | Captain Sonar | Crossfire | Sonar Family | KeyForge: Age of Ascension |
2 | The Last Banquet | Smash Up: Awesome Level 9000 | Smash Up: Monster Smash | Codenames | Smash Up: Cease and Desist | Smash Up: What Were We Thinking? | KeyForge: Call of the Archons | The Magnificent |
3 | Smash Up | BANG! The Dice Game | Ultimate Werewolf | Watson & Holmes | Arkham Horror: The Card Game | Codenames: Disney – Family Edition | Treasure Island | Tuki |
4 | Coup | Crossing | Smash Up: Science Fiction Double Feature | Imagine | Codenames: Pictures | Smash Up: Big in Japan | Smash Up: That '70s Expansion | Aftermath |
5 | Love Letter | Blood Bound | Grog Island | Smash Up: Pretty Pretty Smash Up | Citadels | Whitehall Mystery | Gen7: A Crossroads Game | Era: Medieval Age |
6 | Space Cadets | Smash Up: The Obligatory Cthulhu Set | Saboteur: The Duel | Lost Legacy: Second Chronicle – Vorpal Sword & Whitegold Spire | Codenames: Deep Undercover | Gloomhaven | Shadows: Amsterdam | Smash Up: World Tour – Culture Shock |
7 | Noah | Animals Frightening Night! | Roll for the Galaxy | Mysterium | Black Orchestra | Best of Werewolves of Miller's Hollow | Heroes of Terrinoth | KeyForge: Worlds Collide |
8 | Robinson Crusoe: Adventures on the Cursed Island | Empire Engine | Good Cop Bad Cop | Pathfinder Adventure Card Game: Wrath of the Righteous – Base Set | When I Dream | Legend of the Five Rings: The Card Game | Star Wars: X-Wing (Second Edition) | Wavelength |
9 | Divinare | Two Rooms and a Boom | Istanbul | 504 | New Angeles | Breaking Bad: The Board Game | Smash Up: Oops, You Did It Again | The Lord of the Rings: Journeys in Middle-Earth |
10 | Il Vecchio | Heads Up!: Party Game | Splendor | A Game of Thrones: The Card Game (Second Edition) | Dead of Winter: The Long Night | Indian Summer | Pandemic: Fall of Rome | The Mind Extreme |
11 | Mafia: Vendetta | Anomia: Party Edition | Imperial Settlers | Magic: The Gathering – Arena of the Planeswalkers | Smash Up: It's Your Fault! | This War of Mine: The Board Game | Decrypto | Ninja Academy |
12 | Dixit Jinx | Mascarade | Fields of Arle | RallyRas | Bohnanza: The Duel | Betrayal at Baldur's Gate | Spyfall: Time Travel | Second Chance |
13 | Rumble in the Dungeon | Cappuccino | Dead of Winter: A Crossroads Game | Raptor | Agricola (Revised Edition) | Fallout | Book of Dragons | Smash Up: World Tour – International Incident |
14 | Yedo | Warhammer: Diskwars | Abyss | Aye, Dark Overlord! The Green Box | Game of Thrones: The Iron Throne | Codenames: Duet | Kero | Century: A New World |
15 | Sky Tango | Le Fantôme de l'Opéra | Desperados of Dice Town | Salem 1692 | Cottage Garden | SpyNet | The World of SMOG: Rise of Moloch | Paranormal Detectives |
16 | The Resistance: Avalon | Patchistory | Sheriff of Nottingham | T.I.M.E Stories | Burke's Gambit | Drawing Dead | Exodus: Paris Nouveau | The Only Word: the Party Word Game |
17 | Dixit: Journey | Thunderstone: Starter Set | Akrotiri | My First Bohnanza | Conan | Lovecraft Letter | The Ninth World: A Skillbuilding Game for Numenera | Sierra West |
18 | Mice and Mystics | Thunderstone Advance: Numenera | Fairytale Games: The Battle Royale | Specter Ops | Greedy Greedy Goblins | Santa Maria | Find the Pickle | Draftosaurus |
19 | Mondo Sapiens | Agent Hunter | Deception: Murder in Hong Kong | Mafia de Cuba | Pathfinder Adventure Card Game: Mummy's Mask – Base Set | Sherlock Holmes Consulting Detective: Carlton House & Queen's Park | Human Punishment: Social Deduction 2.0 | Trails of Tucana |
20 | Rex: Final Days of an Empire | Ladies & Gentlemen | Tic Talk | Lost Legacy: Third Chronicle – Sacred Grail & Staff of Dragons | Hit Z Road | Codenames: Marvel | WARIGIN | Nova Luna |
21 | Rent a Hero | Concept | Abracada...What? | Una Notte da Lupi | Danmaku!! | Magic Maze | Spring Meadow | One Key |
22 | Archipelago | The Little Prince: Make Me a Planet | Onitama | Feelinks | DOOM: The Board Game | The Chameleon | Detective Club | Robin of Locksley |
23 | Wits & Wagers Party | Παλέρμο: Το Μεγάλο Ξεκαθάρισμα | Deus | Dungeons & Dragons: Temple of Elemental Evil Board Game | A Feast for Odin | Twilight Imperium: Fourth Edition | Monolith Arena | 5211 |
24 | The Hobbit Card Game | Munchkin Pathfinder | Black Fleet | Los Viajes del Capitán Foucault | Timebomb | Sherlock Holmes Consulting Detective: Vanishing from Hyde Park | Rising Sun | Unlock!: Timeless Adventures |
25 | Stack-A-Biddi | Spyrium | Outfoxed! | One Night Revolution | Hoax (Second Edition) | Cartagena | Unlock!: Secret Adventures – Tombstone Express | TIME Stories Revolution: Damien 1958 NT |
This is an interactive table for the model’s predictions for the training set (from resampling).
We’ll validate the model by looking at its predictions for games published in 2020. That is, how well did a model trained on a user’s collection through 2020 perform in predicting games for the user in 2020?
username | outcome | dataset | method | .metric | .estimate |
daves | owned | validation | Decision Tree | roc_auc | |
daves | owned | validation | GLM | roc_auc |
Table of top 50 games from 2020, highlighting games that the user owns.
Published | ID | Name | Pr(Owned) | Owned |
2020 | 291457 | Gloomhaven: Jaws of the Lion | 0.157 | no |
2020 | 302723 | Forgotten Waters | 0.123 | no |
2020 | 301767 | Mysterium Park | 0.103 | no |
2020 | 292333 | Cowboys II: Cowboys & Indians Edition | 0.091 | no |
2020 | 298572 | Cosmic Encounter Duel | 0.087 | no |
2020 | 296892 | Sacred Rites | 0.086 | no |
2020 | 261403 | Inhuman Conditions | 0.068 | no |
2020 | 300322 | Hallertau | 0.063 | no |
2020 | 301607 | KeyForge: Mass Mutation | 0.062 | no |
2020 | 302425 | Unlock!: Mythic Adventures | 0.062 | no |
2020 | 299592 | Beez | 0.061 | no |
2020 | 246900 | Eclipse: Second Dawn for the Galaxy | 0.060 | no |
2020 | 318983 | Faiyum | 0.059 | no |
2020 | 325611 | Runes of Zun | 0.058 | no |
2020 | 296345 | Sherlock Holmes Consulting Detective: The Baker Street Irregulars | 0.055 | no |
2020 | 295687 | Trust Me, I'm a Doctor | 0.053 | no |
2020 | 317985 | Beyond the Sun | 0.048 | no |
2020 | 300877 | New York Zoo | 0.048 | no |
2020 | 256317 | Guild Master | 0.048 | no |
2020 | 327913 | Unlock!: Timeless Adventures – Arsène Lupin und der große weiße Diamant | 0.042 | no |
2020 | 316377 | 7 Wonders (Second Edition) | 0.042 | no |
2020 | 245658 | Unicorn Fever | 0.042 | no |
2020 | 307997 | Insider Black | 0.041 | no |
2020 | 318472 | Blood Bowl: Second Season Edition | 0.039 | no |
2020 | 313817 | Hello Neighbor: The Secret Neighbor Party Game | 0.038 | no |
2020 | 271524 | TIME Stories Revolution: A Midsummer Night | 0.035 | no |
2020 | 295646 | Spyfest | 0.035 | no |
2020 | 310448 | Zombie Teenz Evolution | 0.035 | no |
2020 | 287742 | TIME Stories Revolution: The Hadal Project | 0.032 | no |
2020 | 294235 | Crime Zoom: His Last Card | 0.032 | no |
2020 | 321305 | Crime Zoom: Bird of Ill Omen | 0.032 | no |
2020 | 321306 | Crime Zoom: A Deadly Writer | 0.032 | no |
2020 | 323784 | Ghost Letters | 0.029 | no |
2020 | 322809 | Diabolik: Heists and Investigations | 0.029 | no |
2020 | 265784 | Cleopatra and the Society of Architects: Deluxe Edition | 0.029 | no |
2020 | 303057 | Pan Am | 0.027 | no |
2020 | 302734 | Master Word | 0.026 | no |
2020 | 314040 | Pandemic Legacy: Season 0 | 0.026 | no |
2020 | 293889 | Fallout Shelter: The Board Game | 0.025 | no |
2020 | 293014 | Nidavellir | 0.025 | no |
2020 | 291874 | Dwergar | 0.024 | no |
2020 | 312762 | The Joker | 0.024 | no |
2020 | 310442 | Feierabend | 0.024 | no |
2020 | 301919 | Pandemic: Hot Zone – North America | 0.023 | no |
2020 | 293141 | King of Tokyo: Dark Edition | 0.022 | no |
2020 | 303669 | Magic Rabbit | 0.022 | no |
2020 | 304285 | Infinity Gauntlet: A Love Letter Game | 0.021 | no |
2020 | 293531 | Detective: A Modern Crime Board Game – Season One | 0.021 | no |
2020 | 303552 | Magic: The Gathering – Unsanctioned | 0.021 | no |
2020 | 300753 | Cross Clues | 0.020 | no |
We can then refit our model to the training and validation set in order to predict all upcoming games for the user.
Examine the top 100 upcoming games, highlighting in blue ones the user already owns.
Published | ID | Name | Pr(Owned) | Owned |
2021 | 344408 | Full Throttle! | 0.123 | no |
2022 | 310873 | Carnegie | 0.114 | no |
2021 | 221298 | NewSpeak | 0.095 | no |
2021 | 339906 | The Hunger | 0.087 | no |
2022 | 349067 | The Lord of the Rings: The Card Game – Revised Core Set | 0.086 | no |
2021 | 316287 | Quest | 0.085 | no |
2021 | 337262 | Fangs | 0.077 | no |
2022 | 331106 | The Witcher: Old World | 0.077 | no |
2021 | 326804 | Rorschach | 0.074 | no |
2022 | 322524 | Bardsung | 0.074 | no |
2021 | 306697 | Smash Up: Marvel | 0.071 | no |
2021 | 331635 | Kameloot | 0.064 | no |
2021 | 340466 | Unfathomable | 0.063 | no |
2021 | 339790 | Cocktail | 0.062 | no |
2021 | 347304 | Time's Up!: Harry Potter | 0.061 | no |
2021 | 316080 | KeyForge: Dark Tidings | 0.057 | no |
2022 | 275284 | Arkeis | 0.056 | no |
2021 | 337389 | Snakesss | 0.056 | no |
2021 | 320136 | Naruto: Ninja Arena | 0.054 | no |
2021 | 341048 | Free Ride | 0.042 | no |
2022 | 283137 | Human Punishment: The Beginning | 0.041 | no |
2021 | 342848 | World of Warcraft: Wrath of the Lich King | 0.040 | no |
2021 | 340237 | Wonder Book | 0.038 | no |
2021 | 319263 | One Card Dungeon | 0.036 | no |
2021 | 309250 | Empyrean Hero: The Card Game | 0.034 | no |
2021 | 285967 | Ankh: Gods of Egypt | 0.034 | no |
2021 | 338834 | MicroMacro: Crime City – Full House | 0.031 | no |
2021 | 331685 | Hit the Silk! | 0.030 | no |
2021 | 304336 | Million Dollar Script | 0.029 | no |
2022 | 251661 | Oathsworn: Into the Deepwood | 0.029 | no |
2021 | 313262 | Shamans | 0.027 | no |
2022 | 349793 | Age of Rome | 0.026 | no |
2021 | 336552 | Mystic Paths | 0.024 | no |
2021 | 322708 | Descent: Legends of the Dark | 0.024 | no |
2021 | 306321 | Night of the Ninja | 0.024 | no |
2022 | 271601 | Feed the Kraken | 0.023 | no |
2022 | 277025 | Vampire: The Masquerade – Chapters | 0.023 | no |
2021 | 343696 | Dune: Betrayal | 0.023 | no |
2022 | 240980 | Blood on the Clocktower | 0.022 | no |
2021 | 336794 | Galaxy Trucker | 0.022 | no |
2022 | 295770 | Frosthaven | 0.022 | no |
2021 | 306169 | MATCH 5 | 0.022 | no |
2021 | 328569 | Mint Bid | 0.022 | no |
2021 | 298069 | Cubitos | 0.021 | no |
2021 | 304324 | Dive | 0.021 | no |
2023 | 274471 | Malhya: Lands of Legends | 0.021 | no |
2021 | 352026 | Dungeon Bowl | 0.021 | no |
2021 | 314491 | Meadow | 0.021 | no |
2022 | 308028 | Drop Drive | 0.020 | no |
2021 | 291847 | Mantis Falls | 0.020 | no |
2021 | 328479 | Living Forest | 0.019 | no |
2022 | 346199 | A Game of Thrones: B'Twixt | 0.019 | no |
2021 | 329450 | Equinox | 0.019 | no |
2021 | 329670 | Pandemic: Hot Zone – Europe | 0.019 | no |
2021 | 273330 | Bloodborne: The Board Game | 0.019 | no |
2022 | 320718 | Hidden Leaders | 0.018 | no |
2021 | 322014 | All-Star Draft | 0.018 | no |
2022 | 351605 | Bohnanza: 25th Anniversary Edition | 0.018 | no |
2021 | 312904 | Conan the Cimmerian: The Tower of the Elephant | 0.018 | no |
2023 | 347909 | Rogue Angels: Legacy of the Burning Suns | 0.017 | no |
2021 | 332944 | Sobek: 2 Players | 0.017 | no |
2021 | 347137 | Chronicles of Avel | 0.016 | no |
2023 | 337627 | Voidfall | 0.016 | no |
2022 | 330592 | Phantom Ink | 0.016 | no |
2021 | 291859 | Riftforce | 0.016 | no |
2021 | 290236 | Canvas | 0.016 | no |
2022 | 344050 | Dubious | 0.016 | no |
2021 | 329845 | Stella: Dixit Universe | 0.016 | no |
2022 | 281549 | Beast | 0.015 | no |
2021 | 334644 | Nicodemus | 0.015 | no |
2021 | 311920 | Ultimate Werewolf: Extreme | 0.015 | no |
2021 | 277700 | Merchants Cove | 0.015 | no |
2022 | 311823 | Nova Aetas Renaissance | 0.015 | no |
2022 | 347702 | Las Vegan | 0.015 | no |
2022 | 345584 | Mindbug | 0.015 | no |
2021 | 338980 | Eastern Empires | 0.014 | no |
2021 | 299255 | Vienna Connection | 0.014 | no |
2021 | 319899 | Decktective: Nightmare in the Mirror | 0.014 | no |
2021 | 329714 | Dreadful Circus | 0.014 | no |
2021 | 308989 | Bristol 1350 | 0.013 | no |
2021 | 331549 | MiniQuest Adventures | 0.013 | no |
2022 | 305096 | Endless Winter: Paleoamericans | 0.013 | no |
2021 | 339263 | Summoner Wars (Second Edition): Starter Set | 0.013 | no |
2022 | 319910 | Pagan: Fate of Roanoke | 0.013 | no |
2021 | 344258 | That Time You Killed Me | 0.013 | no |
2021 | 332800 | Summoner Wars (Second Edition) | 0.013 | no |
2021 | 340041 | Kingdomino Origins | 0.013 | no |
2021 | 249277 | Brazil: Imperial | 0.013 | no |
2021 | 295947 | Cascadia | 0.013 | no |
2022 | 273814 | Deliverance | 0.013 | no |
2022 | 317511 | Tindaya | 0.013 | no |
2021 | 341358 | INSERT | 0.012 | no |
2022 | 342927 | Fire & Stone | 0.012 | no |
2021 | 319792 | Fly-A-Way | 0.012 | no |
2021 | 344114 | Bag of Chips | 0.012 | no |
2021 | 321499 | Get to da Choppa! | 0.012 | no |
2021 | 339484 | Savannah Park | 0.012 | no |
2021 | 338747 | It's Obvious | 0.012 | no |
2021 | 339789 | Welcome to the Moon | 0.012 | no |
2021 | 333144 | Stronghold: Undead (Second Edition) | 0.012 | no |